Off‐ Versus On‐Pump Coronary Surgery and the Effect of Follow‐Up Length and Surgeons’ Experience: A Meta‐Analysis
Bibliographic record
Abstract
Background The debate on the relative benefits of off-pump and on-pump coronary artery bypass surgery ( OPCABG and ONCABG ) is still open. We aimed to provide an updated and complete summary of the evidence on the differences between OPCABG and ONCABG and to explore whether the length of the follow-up and the surgeons' experience in OPCABG modify the comparative results. Methods and Results All randomized clinical trials comparing OPCABG and ONCABG were included. Primary outcome was follow-up mortality. Secondary outcomes were operative mortality, perioperative stroke, perioperative myocardial infarction, and late repeated revascularization. Subgroup analyses were performed based on the length of the follow-up and the percentage of crossover from the OPCABG group (used as a surrogate of surgeon experience with OPCABG ). One hundred four trials were included (20 627 patients, OPCABG : 10 288; ONCABG : 10 339). Weighted mean follow-up time was 3.7 years (range 1-7.5 years). OPCABG was associated with a higher risk of follow-up mortality (incidence rate ratio 1.11, 95% confidence interval 1.00-1.23, P=0.05). The difference was significant only for trials with mean follow-up of ≥3 years and for studies with a crossover rate of ≥10%. There was a trend toward lower risk of perioperative stroke and higher need for late repeated revascularization in the OPCABG arm. Conclusions OPCABG is associated with a higher incidence of incomplete revascularization, an increased need for repeated revascularization, and decreased midterm survival compared with ONCABG . Surgeon inexperience in OPCABG is associated with late mortality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.042 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".